Distributed Energy and Resource Management for Full-Duplex Dense Small Cells for 5G

We consider a multi-carrier and densely deployed small cell network, where small cells are powered by renewable energy source and operate in a full-duplex mode. We formulate an energy and traffic aware resource allocation optimization problem, where a joint design of the beamformers, power and sub-carrier allocation, and users scheduling is proposed. The problem minimizes the sum data buffer lengths of each user in the network by using the harvested energy. A practical uplink user rate-dependent decoding energy consumption is included in the total energy consumption at the small cell base stations. Hence, harvested energy is shared with both downlink and uplink users. Owing to the non-convexity of the problem, a faster convergence sub-optimal algorithm based on successive parametric convex approximation framework is proposed. The algorithm is implemented in a distributed fashion, by using the alternating direction method of multipliers, which offers not only the limited information exchange between the base stations, but also fast convergence. Numerical results advocate the redesigning of the resource allocation strategy when the energy at the base station is shared among the downlink and uplink transmissions.Comment: In Proc. of IEEE IWCMC-2017, Valencia, Spain, Jun. 201

Max-gain relay selection scheme for wireless networks

© 2020 Karabuk University Next generation wireless systems are supposed to handle high amount of data with broader coverage and high quality of service (QoS). When a signal travels from a source to destination, the signal quality may suffer from the fading, which makes it difficult to receive correct messages. To handle the impact of fading, various diversity techniques are performed with Multiple Input Multiple Output (MIMO). Considering cooperative wireless networks, virtual MIMOs are being used, which also called cooperative diversity. In this paper, we propose a max-gain relay selection scheme (MGRS) for buffer-aided wireless cooperative networks. This scheme determines the best link using the maximum gain based on quality of link and available buffer size. The time slot is divided into two parts, one is used to choose the best link from the source to relay transmission (odd slot) and another time slot (even) is used based on the selection of the best link from the relay to destination. Markov chain model is use to measure buffer status and QoS parameters to evaluate the performance. The proposed scheme provides better QoS (12%) compared to the existing relay selection schemes with respect to throughput, end-to-end delay and outage probability

Automatic Localization of Passive Infra-Red Binary Sensors in Home: from Dense to Scattered Network

International audienceLocation of residents in a household is one of the critical information to provide context-aware services. Passive Infra-Red (PIR) binary motion sensors have become the de facto standard technology used in the home by tracking systems due to their low energy consumption and their wide range of coverage. However, installing and managing this network of PIR sensors is difficult for typical residents, such as older adults, with low technical skill. To enable easy deployment of such a system by anybody, we present an extension of a method to automatically identify the location of multiple PIR sensors in a house from the observed motion detection event sequences. Thanks to a floor plan given as prior knowledge, the method estimates the distance between pairs of sensors and identifies particular patterns in the observations to predict the rooms where those sensors are most likely located. The method, which was designed to deal with dense sensors network is adapted to the case of scattered sensors which correspond to most traditional houses. Experimental results on a realistic home show that our method can estimate the location of sensors placed close to the anchor locations with only a few confusions. The experiments also revealed challenges to be addressed to make this method scale to various house configurations

Physical layer security against eavesdropping in the internet of drones (IoD) based communication systems

rones or unmanned aerial vehicles (UAVs) communication technology, which has recently been thoroughly studied and adopted by 3GPP standard (Release 15) due to its dynamic, flexible, and flying nature, is expected to be an integral part of future wireless communications and Internet of drones (IoD) applications. However, due to the unique transmission characteristics and nature of UAV systems including broadcasting, dominant line of site and poor scattering, providing confidentiality for legitimate receivers against unintended ones (eavesdroppers) appears to be a challenging goal to achieve in such scenarios. Besides, the special features of UAVs represented by having limited power (battery-operated) and precessing (light RAM and CPU capabilities), makes applying complex cryptography approaches very challenging and inefficient for such systems. This motives the utilization of alternative approaches enabled by physical layer security (PLS) concept for securing UAV-based systems. Techniques based on PLS are deemed to be promising due to their ability to provide inherent secrecy that is complexity independent, where no matter what computational processing power the eavesdropper may have, there is no way to decrypt the PLS algorithms. This work is dedicated to highlight and overview the latest advances and state of art researches on the field of applying PLS to UAV systems in a unified and structured manner. Particularity, it discusses and explains the different, possible PLS scenarios and use cases of UAVs, which are categorized based on how the drone is utilized and employed in the communication system setup. The main classified categories include the deployment of the flying, mobile UAV as a 1) base station (BS), 2) user equipment (UE), 2) relay, or 4) jammer. Then, recommendations and future open research issues are stated and discussed.No sponso

Microgrid Disaster Resiliency Analysis: Reducing Costs in Continuity of Operations (COOP) Planning

The electric grid serves a vital role in the supply chain of nearly all industrial and commercial organizations. A Microgrid infrastructure can provide this service and beneficial non-emergency services including a variety of generation/energy sources. To demonstrate the applicability of microgrids for energy resiliency, we present a microgrid resiliency case study for United Parcel Service’s (UPS) three separate shipping facilities. The goal, to enhance energy security, minimize cost and prevent cascading losses within other related business units. The impacts and consequences of which are quantified in this study using a Mean Failure Cost (MFC) risk assessment measure. MFC accounts for the potential loses to identified stakeholders that may result from a set of identified failures due to a set of identified threats. In this case, our study uses a method we call All Hazards Econometric System (AHES). AHES incorporates the cost of COOP using a strategy that considers the payback period of microgrid installation as compared to other energy delivery strategies

Towards characterization of edge-cloud continuum

Internet of Things and cloud computing are two technological paradigms that reached widespread adoption in recent years. These paradigms are complementary: IoT applications often rely on the computational resources of the cloud to process the data generated by IoT devices. The highly distributed nature of IoT applications and the giant amounts of data involved led to significant parts of computation being moved from the centralized cloud to the edge of the network. This gave rise to new hybrid paradigms, such as edge-cloud computing and fog computing. Recent advances in IoT hardware, combined with the continued increase in complexity and variability of the edge-cloud environment, led to an emergence of a new vision of edge-cloud continuum: the next step of integration between the IoT and the cloud, where software components can seamlessly move between the levels of computational hierarchy. However, as this concept is very new, there is still no established view of what exactly it entails. Several views on the future edge-cloud continuum have been proposed, each with its own set of requirements and expected characteristics. In order to move the discussion of this concept forward, these views need to be put into a coherent picture. In this paper, we provide a review and generalization of the existing literature on edge-cloud continuum, point out its expected features, and discuss the challenges that need to be addressed in order to bring about this envisioned environment for the next generation of smart distributed applications

Outage Analysis of Energy Harvested Relay-Aided Device-to-Device Communications in Nakagami Channel

In this paper, we obtain a low-complexity closed-form formula for the outage probability of the energy-harvested decode-and-forward (DF) relay-aided underlay Device-to-device (D2D) communications in Nakagami fading channel. By proposing a new idea which finds the power splitting factor in simultaneous wireless information and power transfer (SWIPT) energy-harvesting system such that the transmit power of the relay node in the second time slot is fixed in a pre-defined value, the obtained closed-form expression is valid for both energy-harvested and non-energy-harvested scenarios. This formula is based on n-point generalized Gauss-Laguerre and m-point Gauss-Legendre solutions. It is shown that n is more effective than m for reducing the formula complexity. In addition to a good agreement between the simulation results and numerical analysis based on normalized mean square error (NMSE), it is indicated that (n, m)=(1, 4) and (n, m)=(1, 2) are the appropriate choices, respectively for 0.5≤ µ <0.7 and µ ≥0.7, where µ is the fading factor. As shown in this investigation, increasing the average distance between D2D pairs and cellular user (lower interference), is the reason for decreasing the outage probability. Furthermore, it is clear that increasing the Nakagami fading factor is the reason for decreasing the outage probability

Mobile Health in Remote Patient Monitoring for Chronic Diseases: Principles, Trends, and Challenges

Chronic diseases are becoming more widespread. Treatment and monitoring of these diseases require going to hospitals frequently, which increases the burdens of hospitals and patients. Presently, advancements in wearable sensors and communication protocol contribute to enriching the healthcare system in a way that will reshape healthcare services shortly. Remote patient monitoring (RPM) is the foremost of these advancements. RPM systems are based on the collection of patient vital signs extracted using invasive and noninvasive techniques, then sending them in real-time to physicians. These data may help physicians in taking the right decision at the right time. The main objective of this paper is to outline research directions on remote patient monitoring, explain the role of AI in building RPM systems, make an overview of the state of the art of RPM, its advantages, its challenges, and its probable future directions. For studying the literature, five databases have been chosen (i.e., science direct, IEEE-Explore, Springer, PubMed, and science.gov). We followed the (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) PRISMA, which is a standard methodology for systematic reviews and meta-analyses. A total of 56 articles are reviewed based on the combination of a set of selected search terms including RPM, data mining, clinical decision support system, electronic health record, cloud computing, internet of things, and wireless body area network. The result of this study approved the effectiveness of RPM in improving healthcare delivery, increase diagnosis speed, and reduce costs. To this end, we also present the chronic disease monitoring system as a case study to provide enhanced solutions for RPMsThis research work was partially supported by the Sejong University Research Faculty Program (20212023)S

The Usage of ANN for Regression Analysis in Visible Light Positioning Systems

In this paper, we study the design aspects of an indoor visible light positioning (VLP) system that uses an artificial neural network (ANN) for positioning estimation by considering a multipath channel. Previous results usually rely on the simplistic line of sight model with limited validity. The study considers the influence of noise as a performance indicator for the comparison between different design approaches. Three different ANN algorithms are considered, including Levenberg−Marquardt, Bayesian regularization, and scaled conjugate gradient algorithms, to minimize the positioning error (εp) in the VLP system. The ANN design is optimized based on the number of neurons in the hidden layers, the number of training epochs, and the size of the training set. It is shown that, the ANN with Bayesian regularization outperforms the traditional received signal strength (RSS) technique using the non-linear least square estimation for all values of signal to noise ratio (SNR). Furthermore, in the inner region, which includes the area of the receiving plane within the transmitters, the positioning accuracy is improved by 43, 55, and 50% for the SNR of 10, 20, and 30 dB, respectively. In the outer region, which is the remaining area within the room, the positioning accuracy is improved by 57, 32, and 6% for the SNR of 10, 20, and 30 dB, respectively. Moreover, we also analyze the impact of different training dataset sizes in ANN, and we show that it is possible to achieve a minimum εp of 2 cm for 30 dB of SNR using a random selection scheme. Finally, it is observed that εp is low even for lower values of SNR, i.e., εp values are 2, 11, and 44 cm for the SNR of 30, 20, and 10 dB, respectively

AN EFFICIENT INTERFERENCE AVOIDANCE SCHEME FOR DEVICE-TODEVICE ENABLED FIFTH GENERATION NARROWBAND INTERNET OF THINGS NETWOKS’

Narrowband Internet of Things (NB-IoT) is a low-power wide-area (LPWA) technology built on long-term evolution (LTE) functionalities and standardized by the 3rd-Generation Partnership Project (3GPP). Due to its support for massive machine-type communication (mMTC) and different IoT use cases with rigorous standards in terms of connection, energy efficiency, reachability, reliability, and latency, NB-IoT has attracted the research community. However, as the capacity needs for various IoT use cases expand, the LTE evolved packet core (EPC) system's numerous functionalities may become overburdened and suboptimal. Several research efforts are currently in progress to address these challenges. As a result, an overview of these efforts with a specific focus on the optimized architecture of the LTE EPC functionalities, the 5G architectural design for NB-IoT integration, the enabling technologies necessary for 5G NB-IoT, 5G new radio (NR) coexistence with NB-IoT, and feasible architectural deployment schemes of NB-IoT with cellular networks is discussed. This thesis also presents cloud-assisted relay with backscatter communication as part of a detailed study of the technical performance attributes and channel communication characteristics from the physical (PHY) and medium access control (MAC) layers of the NB-IoT, with a focus on 5G. The numerous drawbacks that come with simulating these systems are explored. The enabling market for NB-IoT, the benefits for a few use cases, and the potential critical challenges associated with their deployment are all highlighted. Fortunately, the cyclic prefix orthogonal frequency division multiplexing (CPOFDM) based waveform by 3GPP NR for improved mobile broadband (eMBB) services does not prohibit the use of other waveforms in other services, such as the NB-IoT service for mMTC. As a result, the coexistence of 5G NR and NB-IoT must be manageably orthogonal (or quasi-orthogonal) to minimize mutual interference that limits the form of freedom in the waveform's overall design. As a result, 5G coexistence with NB-IoT will introduce a new interference challenge, distinct from that of the legacy network, even though the NR's coexistence with NB-IoT is believed to improve network capacity and expand the coverage of the user data rate, as well as improves robust communication through frequency reuse. Interference challenges may make channel estimation difficult for NB-IoT devices, limiting the user performance and spectral efficiency. Various existing interference mitigation solutions either add to the network's overhead, computational complexity and delay or are hampered by low data rate and coverage. These algorithms are unsuitable for an NB-IoT network owing to the low-complexity nature. As a result, a D2D communication based interference-control technique becomes an effective strategy for addressing this problem. This thesis used D2D communication to decrease the network bottleneck in dense 5G NBIoT networks prone to interference. For D2D-enabled 5G NB-IoT systems, the thesis presents an interference-avoidance resource allocation that considers the less favourable cell edge NUEs. To simplify the algorithm's computing complexity and reduce interference power, the system divides the optimization problem into three sub-problems. First, in an orthogonal deployment technique using channel state information (CSI), the channel gain factor is leveraged by selecting a probable reuse channel with higher QoS control. Second, a bisection search approach is used to find the best power control that maximizes the network sum rate, and third, the Hungarian algorithm is used to build a maximum bipartite matching strategy to choose the optimal pairing pattern between the sets of NUEs and the D2D pairs. The proposed approach improves the D2D sum rate and overall network SINR of the 5G NB-IoT system, according to the numerical data. The maximum power constraint of the D2D pair, D2D's location, Pico-base station (PBS) cell radius, number of potential reuse channels, and cluster distance impact the D2D pair's performance. The simulation results achieve 28.35%, 31.33%, and 39% SINR performance higher than the ARSAD, DCORA, and RRA algorithms when the number of NUEs is twice the number of D2D pairs, and 2.52%, 14.80%, and 39.89% SINR performance higher than the ARSAD, RRA, and DCORA when the number of NUEs and D2D pairs are equal. As a result, a D2D sum rate increase of 9.23%, 11.26%, and 13.92% higher than the ARSAD, DCORA, and RRA when the NUE’s number is twice the number of D2D pairs, and a D2D’s sum rate increase of 1.18%, 4.64% and 15.93% higher than the ARSAD, RRA and DCORA respectively, with an equal number of NUEs and D2D pairs is achieved. The results demonstrate the efficacy of the proposed scheme. The thesis also addressed the problem where the cell-edge NUE's QoS is critical to challenges such as long-distance transmission, delays, low bandwidth utilization, and high system overhead that affect 5G NB-IoT network performance. In this case, most cell-edge NUEs boost their transmit power to maximize network throughput. Integrating cooperating D2D relaying technique into 5G NB-IoT heterogeneous network (HetNet) uplink spectrum sharing increases the system's spectral efficiency and interference power, further degrading the network. Using a max-max SINR (Max-SINR) approach, this thesis proposed an interference-aware D2D relaying strategy for 5G NB-IoT QoS improvement for a cell-edge NUE to achieve optimum system performance. The Lagrangian-dual technique is used to optimize the transmit power of the cell-edge NUE to the relay based on the average interference power constraint, while the relay to the NB-IoT base station (NBS) employs a fixed transmit power. To choose an optimal D2D relay node, the channel-to-interference plus noise ratio (CINR) of all available D2D relays is used to maximize the minimum cell-edge NUE's data rate while ensuring the cellular NUEs' QoS requirements are satisfied. Best harmonic mean, best-worst, half-duplex relay selection, and a D2D communication scheme were among the other relaying selection strategies studied. The simulation results reveal that the Max-SINR selection scheme outperforms all other selection schemes due to the high channel gain between the two communication devices except for the D2D communication scheme. The proposed algorithm achieves 21.27% SINR performance, which is nearly identical to the half-duplex scheme, but outperforms the best-worst and harmonic selection techniques by 81.27% and 40.29%, respectively. As a result, as the number of D2D relays increases, the capacity increases by 14.10% and 47.19%, respectively, over harmonic and half-duplex techniques. Finally, the thesis presents future research works on interference control in addition with the open research directions on PHY and MAC properties and a SWOT (Strengths, Weaknesses, Opportunities, and Threats) analysis presented in Chapter 2 to encourage further study on 5G NB-IoT